A Survey on Breast Cancer Detection Using Computational Techniques

Breast cancer accounts for around 25% of all female cancers, making it the most common type of cancer. Breast cancer survival rates can be improved with early detection and diagnosis. However, personalized recommendations for breast cancer diagnosis are frequently insufficient, resulting in missing possibilities for early detection. Another factor is that breast cancer screening and diagnostic tests can be costly and time-consuming. This study intends to make a paradigm shift in the fight against breast cancer by identifying customized treatment, enhancing diagnostic processes, and influencing patients with knowledge by ultimately contributing to higher survival rates. The proposed approach aims to empower individuals and solve the problems associated with late-stage breast cancer diagnoses by analyzing the potential risk factors.